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def main():
env = gym.make('arm_lock-v0')
# build causal planner and get the known and unknown action sequences
data_dir = './scenario_outputs/action_reversal/'
trial_name = 'ex1_extended'
demonstration_file = data_dir + trial_name + '.csv'
perceptual_file = data_dir + 'output_node_' + trial_name + '.mat'
causal_planner = causality.causal_planner.load_trial(demonstration_file, perceptual_file)
# setup .csv headers
col_label = []
col_label.append('frame')
for col_name in env.world_def.get_internal_state()['OBJ_STATES']:
col_label.append(col_name)
col_label.append('agent')
for col_name in env.action_space:
col_label.append(col_name)
index_map = {name : idx for idx, name in enumerate(col_label)}
results = [col_label]
i = 0
# append initial observation